Neural network models offer a totally new approach to intelligent information processing that is robust, fault tolerant, and can be extremely fast. Such neural networks are discussed, for example, in A. P. Thakoor et al, "Binary Synaptic Connections Based on Memory Switching in a-Si:H", Neural Networks for Computing, J. S. Denker, Ed., American Institute of Physics Conference Proceedings .notlessthan.151, Snowbird, UT, pp. 426-431 (1986).
The aforementioned features originate directly from the massive interconnectivity of neurons (the decision-making elements) in the brain and its ability to store information in a distributed manner as a large number of synaptic interconnects of varying strengths. Hardware implementations of neural network concepts, therefore, are attracting considerable attention. Such artificial neural networks are expected, for example, to function as high speed, content addressable, associative memories in large knowledge bases for artificial intelligence applications and robotics or to perform complex computational tasks such as combinatorial optimization for autonomous systems.
In particular, electronic implementation of an associative memory based on neural network models requires large arrays of extremely simple, binary connection elements or synaptic interconnects. Information is essentially stored in the binary states of the interconnects. Non-volatile storage of information therefore can take place at the time of fabrication of the synaptic array by making the resistive state of the desired interconnect "ON" or "OFF". Alternatively, significantly more useful memory systems can be built if programmable, binary resistive thin film devices (non-volatile microswitches) are used as synaptic interconnects.
Non-volatile, programmable, associative electronic memories based upon neural network models, with dense synaptic interconnection arrays in thin-film form, have recently been developed, using memory switching in hydrogenated amorphous silicon (a-Si:H). The highly parallel nature of neural network circuits requires the "ON" connections in large synaptic arrays to have very weak connection strengths (&gt;10.sup.6 .OMEGA. for 1000.times.1000 matrix). Such weak connections are needed to limit the current in the wires to a reasonable density (to avoid electromigration) as well as the overall power dissipation.
Irreversible (OFF.fwdarw.ON) memory switching in existing hydrogenated amorphous silicon (a-Si:H) thin films, however, results in an uncontrollable "ON" state resistance (&lt;10.sup.6 .OMEGA.), which makes them inappropriate for their use as programmable, binary weak synaptic interconnections with any precision. A current limiting (synaptic) resistance (.apprxeq.10.sup.6 .OMEGA.) is required in series with such switching materials to obtain the desired "ON" resistance of the node when switched, which in turn complicates the microswitch structure.